The subject matter disclosed herein relates to X-ray imaging systems, and more specifically to digital X-ray imaging systems.
Patient imaging systems are commonly used by medical professionals to examine and diagnose patients. Generally speaking, when performing an X-ray exam, a patient is typically located between an X-ray source and detector that are designed to collect X-ray attenuation data as the patient is imaged. The various paths that X-rays traverse from the X-ray source, through the patient, and to the X-ray detector define a field of view for each projection acquired. However, since the detector is often an expensive component to manufacture, where the cost increases with increasing detector size, a detector may be utilized that is smaller than the patient being imaged. Additionally, the detector may be placed at a distance away from the patient to allow the source and detector sufficient space to move with respect to the patient. This spacing also serves to limit the inadvertent detection of X-rays that have been scattered by the patient's tissue.
Thus, in view of the limited size of the detector, the field of view for each projection may not completely span the patient's dimensions that need to be imaged, omitting information near the edges of the field of view. As a result, while projection data gleaned from patient tissue located near the center of the field of view may be relatively complete, the incompleteness of the projection data near the edges of the field of view may produce artifacts and distortions in the resulting images as a consequence of the image reconstruction algorithm attempting to properly represent the patient's tissue from an incomplete set of projection data. For example, during a patient examination involving imaging of a patient's chest cavity, portions of the patient's arm may be within the field of view for some projections and not others, providing the image reconstruction algorithm with incomplete or ambiguous projection data regarding the location and density of the patient's arm. As a result, the image reconstruction algorithm must resolve this ambiguity and determine how to incorporate the incomplete projection data into the remainder of the patient's projection data. This can result in an image with, for example, streaking artifacts near the center and/or ringing artifacts near the edges of the resulting images.
Therefore, it would be beneficial to optimize the field of view during patient imaging in order to provide the image reconstruction algorithm with the most complete projection data set possible.